Literature DB >> 20570381

Improving target delineation on 4-dimensional CT scans in stage I NSCLC using a deformable registration tool.

Iris E van Dam1, John R van Sörnsen de Koste, Gerard G Hanna, Rebecca Muirhead, Ben J Slotman, Suresh Senan.   

Abstract

INTRODUCTION: Correct target definition is crucial in stereotactic radiotherapy for lung tumors. We evaluated use of deformable registration (DR) for target contouring on 4-dimensional (4D) CT scans.
MATERIALS AND METHODS: Three clinicians contoured gross tumor volume (GTV) in an end-inspiration phase of 4DCT of 6 patients on two occasions. Two clinicians contoured GTVs in all phases of 4DCT and on maximum intensity projections (MIP). The initial GTV was auto-propagated to 9 other phases using a B-spline algorithm (VelocityAI). Internal target volumes (ITVs) generated were (i) ITV(10manual) encompassing all physician-contoured GTVs, (ii) ITV-MIP(optimized) from MIP after review of individual 4DCT phases, (iii) ITV(10deformed) encompassing auto-propagated GTVs using DR, and (iv) ITV(10deformed-optimized), from an ITV(10deformed) target that was modified to form a 'clinically optimal' ITV. Volume-overlaps were scored using Dice's Similarity Coefficients (DSCs).
RESULTS: Intra-clinician GTV reproducibility was greater than inter-clinician reproducibility (mean DSC 0.93 vs. 0.88, p<0.0004). In five of 6 patients, ITV-MIP(optimized) differed from the ITV(10deformed-optimized). In all patients, the DSC between ITV(10deformed-optimized) and ITV(10deformed) was higher than that between ITV(10deformed-optimized) and ITV-MIP(optimized) (p<0.02 T-test).
CONCLUSION: ITVs created in stage I tumors using DR were closer to 'clinically optimal' ITVs than was the case with a MIP-modified approach. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

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Year:  2010        PMID: 20570381     DOI: 10.1016/j.radonc.2010.05.003

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  23 in total

1.  Radiomics in peritumoral non-enhancing regions: fractional anisotropy and cerebral blood volume improve prediction of local progression and overall survival in patients with glioblastoma.

Authors:  Jung Youn Kim; Min Jae Yoon; Ji Eun Park; Eun Jung Choi; Jongho Lee; Ho Sung Kim
Journal:  Neuroradiology       Date:  2019-07-09       Impact factor: 2.804

Review 2.  Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications.

Authors:  Kaustav Bera; Vamsidhar Velcheti; Anant Madabhushi
Journal:  Am Soc Clin Oncol Educ Book       Date:  2018-05-23

Review 3.  Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging.

Authors:  E Sala; E Mema; Y Himoto; H Veeraraghavan; J D Brenton; A Snyder; B Weigelt; H A Vargas
Journal:  Clin Radiol       Date:  2016-10-11       Impact factor: 2.350

4.  Dynamic CT imaging of volumetric changes in pulmonary nodules correlates with physical measurements of stiffness.

Authors:  Frederick M Lartey; Marjan Rafat; Mohammadreza Negahdar; Andrey V Malkovskiy; Xinzhe Dong; Xiaoli Sun; Mei Li; Timothy Doyle; Jayakumar Rajadas; Edward E Graves; Billy W Loo; Peter G Maxim
Journal:  Radiother Oncol       Date:  2016-12-15       Impact factor: 6.280

5.  Semiautomated volumetric response evaluation as an imaging biomarker in superior sulcus tumors.

Authors:  C G Vos; M Dahele; J R van Sörnsen de Koste; S Senan; I Bahce; M A Paul; E Thunnissen; E F Smit; K J Hartemink
Journal:  Strahlenther Onkol       Date:  2013-12-22       Impact factor: 3.621

6.  Contour propagation using non-uniform cubic B-splines for lung tumor delineation in 4D-CT.

Authors:  Yongchuan Liu; Renchao Jin; Mi Chen; Enmin Song; Xiangyang Xu; Sheng Zhang; Chih-Cheng Hung
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-07-16       Impact factor: 2.924

7.  Automatic assessment of average diaphragm motion trajectory from 4DCT images through machine learning.

Authors:  Guang Li; Jie Wei; Hailiang Huang; Carl Philipp Gaebler; Amy Yuan; Joseph O Deasy
Journal:  Biomed Phys Eng Express       Date:  2015-12-29

8.  Evaluation of 4-dimensional computed tomography to 4-dimensional cone-beam computed tomography deformable image registration for lung cancer adaptive radiation therapy.

Authors:  Salim Balik; Elisabeth Weiss; Nuzhat Jan; Nicholas Roman; William C Sleeman; Mirek Fatyga; Gary E Christensen; Cheng Zhang; Martin J Murphy; Jun Lu; Paul Keall; Jeffrey F Williamson; Geoffrey D Hugo
Journal:  Int J Radiat Oncol Biol Phys       Date:  2013-02-22       Impact factor: 7.038

9.  Quantitative radiomic model for predicting malignancy of small solid pulmonary nodules detected by low-dose CT screening.

Authors:  Liting Mao; Huan Chen; Mingzhu Liang; Kunwei Li; Jiebing Gao; Peixin Qin; Xianglian Ding; Xin Li; Xueguo Liu
Journal:  Quant Imaging Med Surg       Date:  2019-02

Review 10.  A review of automatic lung tumour segmentation in the era of 4DCT.

Authors:  Nadine Wong Yuzhen; Sarah Barrett
Journal:  Rep Pract Oncol Radiother       Date:  2019-02-22
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